WO2023203970A1 - Système de planification d'imagerie et procédé de planification d'imagerie - Google Patents

Système de planification d'imagerie et procédé de planification d'imagerie Download PDF

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WO2023203970A1
WO2023203970A1 PCT/JP2023/012263 JP2023012263W WO2023203970A1 WO 2023203970 A1 WO2023203970 A1 WO 2023203970A1 JP 2023012263 W JP2023012263 W JP 2023012263W WO 2023203970 A1 WO2023203970 A1 WO 2023203970A1
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imaging
dag
node
processing unit
planning
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PCT/JP2023/012263
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English (en)
Japanese (ja)
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広宣 森
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日本電気株式会社
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64G—COSMONAUTICS; VEHICLES OR EQUIPMENT THEREFOR
    • B64G1/00—Cosmonautic vehicles
    • B64G1/10—Artificial satellites; Systems of such satellites; Interplanetary vehicles

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  • the present invention relates to an imaging planning system and an imaging planning method, and particularly to an imaging planning system and an imaging planning method that determine the allocation of imaging points among a plurality of satellites and the order of imaging.
  • a single orbiting satellite hereinafter also simply referred to as a satellite
  • the imaging order of multiple points is expressed as a DAG (Directed Acyclic Graph). It can be obtained by finding the longest path from .
  • DAG Directed Acyclic Graph
  • FIG. 15 is an explanatory diagram showing an example of formulating an imaging plan using one satellite. As shown in the left part of FIG. 15, in this example, a case is considered in which a plan is created for one orbiting satellite to image imaging points 1 to 5 on the earth.
  • the imaging order of imaging points 1 to 5 of the orbiting satellite is expressed as DAG.
  • the nodes (circles) configuring the DAG shown in FIG. 15 represent imaging points.
  • the edges (arrows) forming the DAG shown in FIG. 15 represent the order in which images can be captured. Note that the meaning of each notation is the same in other figures.
  • the order in which images can be taken is expressed by edges, taking into account the constraints of orbiting satellites.
  • DAG shown in FIG. 15 indicates that the orbiting satellite can image imaging point 3 or imaging point 5 next to imaging point 1.
  • DAG shown in FIG. 15 indicates that the orbiting satellite can image imaging point 4 or imaging point 5 next to imaging point 2. Further, DAG shown in FIG. 15 indicates that the orbiting satellite can image the imaging point 4 or the imaging point 5 next to the imaging point 3.
  • weights of the nodes configuring the DAG shown in FIG. 15 mean that the larger the value, the more prioritized the node represents the imaging point.
  • the weights of imaging points 1 to 5 are "1", “2", “2”, “1", and "1", respectively.
  • the orbiting satellite can image the largest number of imaging points.
  • the order in which the sum of weights is the largest, that is, the longest path in DAG is "imaging point 1 ⁇ imaging point 3 ⁇ imaging point 4.”
  • an imaging plan is created using DAG, an imaging plan that images more imaging points is created.
  • Patent Document 1 describes that it is possible to use a one-to-one synchronous communication API (Application Programming Interface) without causing deadlock in inter-task synchronous communication in a process configured by multiple tasks and synchronous communication.
  • the task communication method is described.
  • Patent Document 2 describes a method for determining an image layout, which includes the step of accessing a plurality of image elements having one ordered sequence.
  • Patent Document 3 describes a method for spacecraft that is optimal for matching local constraints and cumulative constraints of a spacecraft, and that enables consideration of a ground area that needs to be acquired multiple times or once. A method for planning image acquisition of terrestrial regions is described.
  • Constellation operations are also being carried out in which not only one satellite but also multiple satellites take images at high frequency.
  • planning an imaging plan using multiple satellites is a complex and time-consuming task.
  • FIG. 16 is an explanatory diagram illustrating issues when creating an imaging plan using multiple satellites.
  • FIG. 16 shows DAG representing the imaging order of satellite 1 and DAG representing the imaging order of satellite 2.
  • the two imaging points 1 shown in FIG. 16 have different imaging satellites and different imaging times. Even if the imaging point is the same, if the imaging satellite and imaging time are different, it is impossible to treat it as one node.
  • imaging point 2 shown in FIG. 16 and other imaging points can both be imaged even if the imaging time is the same, as long as the imaging satellites are different. Therefore, a condition is imposed on the imaging point 2 shown in FIG. 16 and other imaging points that "both can be imaged in the same time period.”
  • Patent Documents 1 to 3 do not describe a technique for creating an imaging plan using a plurality of satellites using DAG.
  • the method of improving the performance of multiple cores is more mainstream than the method of improving the performance of a single CPU (Central Processing Unit) core. That is, in order to speed up the planning of an imaging plan, it is important to make the planning logic a logic that can be easily parallelized.
  • CPU Central Processing Unit
  • an object of the present invention is to provide an imaging planning system and an imaging planning method that can quickly create an imaging plan using a plurality of satellites.
  • the imaging planning system is an imaging planning system including a planning unit that creates an imaging plan in which a plurality of satellites take images of a plurality of imaging points, and the planning unit includes a planning unit that creates an imaging plan in which a plurality of satellites take images of a plurality of imaging points.
  • One DAG is generated by combining DAGs representing the imaging order for imaging a point so that a predetermined condition is satisfied across multiple satellites, and topological sorting is performed on the generated one DAG. , is characterized by obtaining the longest path in one DAG that has been topologically sorted.
  • the imaging planning method is an imaging planning method executed in an imaging planning system that creates an imaging plan in which a plurality of satellites image a plurality of imaging points.
  • One DAG is generated by combining DAGs representing the imaging order in which satellites take images of multiple imaging points so that a predetermined condition is satisfied across multiple satellites, and the resulting one DAG is
  • the method is characterized in that it performs topological sorting and obtains the longest path in one DAG that has been topologically sorted.
  • a computer-readable recording medium having recorded thereon an imaging planning program according to the present invention when executed by a computer, allows one artificial satellite to create an imaging plan in which a plurality of satellites image a plurality of imaging points.
  • One DAG is generated by combining DAGs representing the imaging order in which multiple imaging points are imaged so that a predetermined condition is satisfied across multiple satellites, and for one generated DAG
  • An imaging planning program that performs topological sorting and obtains the longest path in one DAG that has been topologically sorted is stored.
  • an imaging plan using a plurality of satellites can be formulated at high speed.
  • FIG. 1 is a block diagram showing a configuration example of an imaging planning system according to an embodiment of the present invention.
  • FIG. 7 is a flowchart showing the operation of imaging planning processing by the imaging planning system 100 of the present embodiment.
  • 3 is a flowchart showing the operation of DAG combination processing by the imaging plan generation processing unit 110 of the present embodiment.
  • FIG. 6 is an explanatory diagram showing an example of arranging nodes constituting each DAG in a grid pattern by the imaging plan generation processing unit 110.
  • FIG. 3 is an explanatory diagram showing an example of connecting nodes by the imaging plan generation processing unit 110 to nodes of other satellites.
  • FIG. 6 is an explanatory diagram showing another example of connecting nodes by the imaging plan generation processing unit 110 with nodes of other satellites.
  • FIG. 7 is a flowchart showing the operation of route generation processing by the imaging plan generation processing unit 110 of the present embodiment.
  • FIG. 4 is an explanatory diagram showing an example in which topological sorting is performed on DAG by the imaging plan generation processing unit 110. It is a flowchart which shows operation of general node score update processing.
  • 7 is a flowchart showing the operation of node score update processing by the imaging plan generation processing unit 110 of the present embodiment.
  • 7 is a flowchart showing the operation of imaging order acquisition processing by the imaging plan generation processing unit 110 of the present embodiment.
  • 6 is an explanatory diagram showing an example of deleting a node from the longest route by the imaging plan generation processing unit 110.
  • FIG. 1 is an explanatory diagram showing an example of the hardware configuration of an imaging planning system 100 according to the present invention.
  • FIG. 1 is a block diagram showing an overview of an imaging planning system according to the present invention.
  • FIG. 2 is an explanatory diagram showing an example of formulating an imaging plan using one satellite.
  • FIG. 2 is an explanatory diagram illustrating issues when planning an imaging plan using multiple satellites.
  • FIG. 1 is a block diagram showing a configuration example of an imaging planning system according to an embodiment of the present invention.
  • the imaging planning system 100 of this embodiment includes an imaging plan generation processing section 110.
  • the imaging planning system 100 of this embodiment expresses the order in which multiple satellites take images in parallel using a DAG, and uses a method to solve the longest route that incorporates a mechanism to avoid duplication, so that multiple imaging points can be It is possible to quickly formulate a plan to share images with multiple orbiting satellites.
  • a case will be considered in which a plan is created in which a plurality of orbiting satellites share images of a plurality of imaging points on the earth.
  • a DAG representing the order in which images are taken at multiple imaging points is prepared as input data for each orbiting satellite.
  • the imaging plan generation processing unit 110 of this embodiment combines the prepared DAGs for each orbiting satellite. Next, the imaging plan generation processing unit 110 calculates the longest route and obtains the imaging points and imaging order assigned to each satellite. As shown in FIG. 1, the imaging plan generation processing unit 110 outputs data indicating the imaging order of imaging points of each satellite as output data.
  • FIG. 2 is a flowchart showing the operation of imaging planning processing by the imaging planning system 100 of this embodiment.
  • the imaging plan generation processing unit 110 of the imaging planning system 100 receives a plurality of input data each indicating a DAG for each satellite (step S110).
  • the imaging plan generation processing unit 110 executes a DAG combination process that combines the DAGs for each satellite indicated by the plurality of input data into one DAG (step S120).
  • the imaging plan generation processing unit 110 executes a route generation process to obtain the longest route from the DAGs combined in step S120 (step S130).
  • the imaging plan generation processing unit 110 executes imaging order acquisition processing to obtain the imaging order for each satellite from the longest route determined in step S130 (step S140).
  • the imaging plan generation processing unit 110 outputs the imaging order for each satellite determined in step S140 (step S150). After outputting the imaging order for each satellite, the imaging planning system 100 ends the imaging planning process.
  • FIG. 3 is a flowchart showing the operation of DAG combination processing by the imaging plan generation processing unit 110 of this embodiment.
  • the imaging plan generation processing unit 110 arranges the nodes forming each DAG in a grid pattern in descending order of imaging time (step S121).
  • the imaging plan generation processing unit 110 connects all the arranged nodes to nodes of other satellites in order of earliest imaging time (step S122). After the connection, the imaging plan generation processing unit 110 returns to the imaging planning process shown in FIG. 2 .
  • FIG. 4 is an explanatory diagram showing an example of arranging nodes constituting each DAG in a grid pattern by the imaging plan generation processing unit 110.
  • FIG. 4 shows an example in which the imaging plan generation processing unit 110 arranges nodes constituting each DAG of satellites 1 to m in step S121.
  • the imaging plan generation processing unit 110 arranges the nodes forming the DAG in the order of imaging times t 1 to t n from the top. Furthermore, the imaging plan generation processing unit 110 arranges a plurality of nodes having the same imaging time in a horizontal line. The imaging plan generation processing unit 110 performs the above-described arrangement processing for each DAG.
  • FIG. 5 is an explanatory diagram showing an example of connecting nodes with nodes of other satellites by the imaging plan generation processing unit 110.
  • FIG. 5 shows an example in which the imaging plan generation processing unit 110 connects nodes forming each DAG of satellite 1 and satellite 2 in step S122.
  • the imaging plan generation processing unit 110 selects, as a connection destination, a node whose imaging time is the same as that of the connection source node, or a node whose imaging time is in the future, among nodes of other satellites. As indicated by the dashed arrow in FIG. 5, the imaging plan generation processing unit 110 does not select a node whose imaging time is earlier than the imaging time of the connection source node as a connection destination.
  • the imaging plan generation processing unit 110 when connecting to a connection destination node with the same imaging time, copies the connection destination node and output edges (only edges output to nodes on the same satellite). Next, the imaging plan generation processing unit 110 connects the connection source node, the copied connection destination node, and the copied output edge, respectively.
  • the imaging plan generation processing unit 110 when connecting to a connection destination node whose imaging time is in the future, the imaging plan generation processing unit 110 directly connects the connection source node and the connection destination node.
  • the imaging plan generation processing unit 110 can express the order in which multiple satellites take images in parallel as DAG.
  • FIG. 5 shows an example in which the imaging plan generation processing unit 110 connects the nodes forming the DAG of the satellite 1 to the nodes forming the DAG of the satellite 2.
  • the imaging plan generation processing unit 110 can similarly connect in the opposite direction, that is, from the nodes forming the DAG of the satellite 2 to the nodes forming the DAG of the satellite 1.
  • FIG. 6 is an explanatory diagram showing another example of connecting nodes by the imaging plan generation processing unit 110 with nodes of other satellites.
  • the imaging plan generation processing unit 110 selects a connected node for each row. , perform the operation to connect.
  • the imaging plan generation processing unit 110 connects the nodes forming the DAG of the satellite 1 to the nodes of the column 1 and the column 2 forming the DAG of the satellite 2, respectively.
  • the method of connecting nodes by the imaging plan generation processing section 110 shown in FIG. 6 is the same as the method of connecting nodes by the imaging plan generation processing section 110 shown in FIG. 5.
  • FIG. 7 is a flowchart showing the operation of route generation processing by the imaging plan generation processing unit 110 of this embodiment.
  • the imaging plan generation processing unit 110 combines the plurality of start nodes and the plurality of end nodes in one DAG generated in step S120 into one. After combining, the imaging plan generation processing unit 110 performs topological sorting on one generated DAG (step S131).
  • the imaging plan generation processing unit 110 updates the scores of the nodes to the maximum value in the order of topological sorting, from the start node that is grouped together to the end node that is grouped together (step S132).
  • the imaging plan generation processing unit 110 generates the longest route by tracing the input source nodes recorded in the nodes from the end nodes that are grouped together toward the start nodes that are grouped together (step S133).
  • the imaging plan generation processing unit 110 After generating the longest route, the imaging plan generation processing unit 110 returns to the imaging plan creation process shown in FIG. 2.
  • the method of topologically sorting DAGs and then finding the longest path, as shown in FIG. 7, is a general method of finding the longest path from DAGs.
  • FIG. 8 is an explanatory diagram showing an example in which the imaging plan generation processing unit 110 performs topological sorting on DAG.
  • FIG. 8 shows an example in which the imaging plan generation processing unit 110 performs topological sorting in step S131. Note that FIG. 8 shows some of the nodes and edges that constitute the DAG.
  • the imaging plan generation processing unit 110 combines the plurality of start nodes and the plurality of end nodes in one DAG generated in step S120 into one.
  • the two rounded rectangles shown in FIG. 8 represent a start node and an end node, respectively.
  • the imaging plan generation processing unit 110 After combining each of the multiple start nodes and multiple end nodes into one, the imaging plan generation processing unit 110 performs topological sorting on the DAG.
  • the right part of Figure 8 shows the DAG that has been topologically sorted.
  • the imaging plan generation processing unit 110 generally calculates the score of the node by "score of the input source node + weight of the input source node".
  • FIG. 9 is a flowchart showing the operation of a general node score update process.
  • the main body of each process shown in FIG. 9 is the imaging plan generation processing unit 110.
  • the imaging plan generation processing unit 110 initializes the scores of all nodes forming the DAG to 0 (step S001). Next, the imaging plan generation processing unit 110 enters a node loop (step S002).
  • the imaging plan generation processing unit 110 which has entered the node loop, extracts one node whose score has not been updated yet from the topologically sorted DAG. That is, the imaging plan generation processing unit 110 enters an edge loop (step S003).
  • the imaging plan generation processing unit 110 which has entered the edge loop, extracts one input edge that has not been processed yet from among the input edges to the extracted node.
  • the input source node is recorded in the input edge.
  • the imaging plan generation processing unit 110 determines whether the score of the extracted node is smaller than the sum of the "score of the input source node” and the "weight of the input source node” recorded in the extracted input edge. (Step S004).
  • the imaging plan generation processing unit 110 returns to the process of step S003 and generates the next input. Process edges.
  • the imaging plan generation processing unit 110 sets the score of the node to the "score of the input source node + the weight of the input source node".
  • the weight of the input source node is updated to "the weight of the input source node" (step S005).
  • the imaging plan generation processing unit 110 updates the input source node for the extracted node to the input source node recorded in the extracted input edge (step S006). After updating, the imaging plan generation processing unit 110 returns to the process of step S003 and processes the next input edge.
  • the imaging plan generation processing unit 110 repeatedly executes the processes of steps S004 to S006 until all input edges to the extracted nodes are processed. When all input edges to the extracted node have been processed, the imaging plan generation processing unit 110 exits the edge loop (step S007).
  • the imaging plan generation processing unit 110 repeatedly executes the processes of steps S003 to S007 in the order of the topologically sorted nodes until the scores of all the topologically sorted nodes are updated.
  • the imaging plan generation processing unit 110 exits the node loop (step S008). Upon exiting the node loop, the imaging plan generation processing unit 110 ends the node score update processing.
  • FIG. 10 is a flowchart showing the operation of node score update processing by the imaging plan generation processing unit 110 of this embodiment.
  • the imaging plan generation processing unit 110 initializes the scores of all nodes forming the DAG to 0 (step S901). Next, the imaging plan generation processing unit 110 enters a node loop (step S902).
  • the imaging plan generation processing unit 110 which has entered the node loop, extracts one node whose score has not been updated yet from the topologically sorted DAG. That is, the imaging plan generation processing unit 110 enters an edge loop (step S903).
  • the imaging plan generation processing unit 110 which has entered the edge loop, extracts one input edge that has not been processed yet from among the input edges to the extracted node.
  • the input source node is recorded in the input edge.
  • the imaging plan generation processing unit 110 determines whether the satellite that images the extracted node is different from the satellite that images the input source node recorded in the extracted input edge (step S904).
  • the "satellite that images the node” is referred to as the "satellite of the node" in FIG.
  • the imaging plan generation processing unit 110 If the satellite that images the extracted node and the satellite that images the input source node recorded in the extracted input edge are different (True in step S904), the imaging plan generation processing unit 110 The input source nodes of the recorded input source nodes are traced in order. By sequentially tracing the input source nodes, the imaging plan generation processing unit 110 searches for a node that is imaged by the same satellite that images the extracted node (step S905).
  • step S906 If a node imaged by the same satellite is not searched for (No in step S906), the imaging plan generation processing unit 110 proceeds to the process of step S908.
  • the imaging plan generation processing unit 110 determines whether or not it is impossible to image the node from which the satellite was taken out next to the searched node. (Step S907).
  • the imaging plan generation processing unit 110 returns to the process of step S903 and processes the next input edge.
  • step S907 If the satellite can image the extracted node (No in step S907), the imaging plan generation processing unit 110 proceeds to the process of step S908.
  • the imaging plan generation processing unit 110 initializes the variable weight with 0. (step S908).
  • the imaging plan generation processing unit 110 sequentially traces the input source nodes recorded in the extracted input edge. By sequentially tracing the input source nodes, the imaging plan generation processing unit 110 searches for a node indicating the same imaging point as the one indicated by the extracted node (step S909).
  • step S910 If a node indicating the same imaging point is not searched (No in step S910), the imaging plan generation processing unit 110 proceeds to the process of step S912.
  • the imaging plan generation processing unit 110 sets the weight of the searched node indicating the same imaging point to the variable weight (step S911).
  • the imaging plan generation processing unit 110 calculates the score of the extracted node as the difference between the sum of the "input source node score” and the "input source node weight” recorded in the extracted input edge, and the variable weight. It is determined whether it is smaller than (step S912).
  • the imaging plan generation processing unit 110 performs the processing in step S903. Go back and process the next input edge.
  • the imaging plan generation processing unit 110 sets the score of the node to the "input source node weight". "Score of source node + weight of input source node - variable weight” (step S913).
  • the imaging plan generation processing unit 110 updates the input source node for the extracted node to the input source node recorded in the extracted input edge (step S914). After updating, the imaging plan generation processing unit 110 returns to the process of step S903 and processes the next input edge.
  • the imaging plan generation processing unit 110 repeatedly executes the processing of steps S904 to S914 until all input edges to the extracted nodes are processed. When all input edges to the extracted node have been processed, the imaging plan generation processing unit 110 exits the edge loop (step S915).
  • the imaging plan generation processing unit 110 repeatedly executes the processes of steps S903 to S915 in the order of the topologically sorted nodes until the scores of all the topologically sorted nodes are updated.
  • the imaging plan generation processing unit 110 exits the node loop (step S916). Upon exiting the node loop, the imaging plan generation processing unit 110 ends the node score update processing.
  • the imaging plan generation processing unit 110 of this embodiment updates the score of the node and the input source node of the node by executing the node score update process shown in FIG. 10 in step S132.
  • the imaging plan generation processing unit 110 can calculate the longest route from the DAG in step S133.
  • steps S004 to S006 shown in FIG. 9 is changed to the processing in steps S904 to S914 shown in FIG. 10.
  • the above changes are made to satisfy the condition that "only one image can be captured” and the condition that "both images can be captured in the same time period" shown in FIG. 16.
  • FIG. 11 is a flowchart showing the operation of the imaging order acquisition process by the imaging plan generation processing unit 110 of this embodiment.
  • the imaging plan generation processing unit 110 traces the longest path determined in step S130 from the end node to the start node. If a node indicating an existing imaging point is detected during tracing, the imaging plan generation processing unit 110 deletes the detected node (step S141).
  • the imaging plan generation processing unit 110 classifies the nodes remaining on the longest route for each satellite.
  • the imaging plan generation processing unit 110 arranges the nodes classified by satellite in descending order of imaging time (step S142).
  • the imaging plan generation processing unit 110 can determine the imaging order for each satellite. After determining the imaging order for each satellite, the imaging plan generation processing unit 110 returns to the imaging plan creation process shown in FIG. 2.
  • FIG. 12 is an explanatory diagram showing an example of deleting a node from the longest route by the imaging plan generation processing unit 110.
  • FIG. 12 shows an example in which the imaging plan generation processing unit 110 deletes duplicate nodes in step S141.
  • the two circles labeled "1" represent two nodes indicating the same imaging point. While tracing the longest route from the end node to the start node, the imaging plan generation processing unit 110 detects a node indicating an existing imaging point, and as shown in the right part of FIG. Delete the second circle.
  • the imaging planning system 100 of this embodiment is an imaging planning system that includes the imaging plan generation processing unit 110 that creates an imaging plan in which a plurality of satellites image a plurality of imaging points.
  • the imaging plan generation processing unit 110 creates one DAG by combining DAGs representing the imaging order in which one artificial satellite images multiple imaging points so that a predetermined condition is satisfied across the multiple satellites. generate, perform topological sorting on one generated DAG, and obtain the longest path in the topologically sorted DAG.
  • the predetermined condition is that no closed circuit is generated.
  • the imaging plan generation processing unit 110 classifies the plurality of imaging points constituting the acquired longest route for each satellite to be imaged, and performs processing for arranging the classified plurality of imaging points in order of imaging time for each artificial satellite. An imaging plan is created by executing each. Furthermore, the imaging plan generation processing unit 110 deletes the imaging point with an earlier imaging time among the overlapping imaging points on the acquired longest route.
  • the imaging plan generation processing unit 110 calculates the score of the node that constitutes one DAG that has undergone topological sorting and indicates the imaging point, and the input source node of the node that constitutes one DAG. Calculate for each.
  • the imaging plan generation processing unit 110 calculates the score of the node and the input source node of the node so that the condition that only one node among the plurality of nodes indicating the same imaging point can be imaged is satisfied.
  • the imaging plan generation processing unit 110 calculates the score of the node and the input source node of the node so that the condition that a plurality of nodes indicating different imaging points can all be imaged at the same imaging time is satisfied.
  • a DAG representing the imaging order of one artificial satellite may include multiple columns in which multiple imaging points are arranged in order of imaging time.
  • the imaging plan generation processing unit 110 of this embodiment may replace the DAG for each satellite with the DAG for each path. By replacing them, the imaging plan generation processing unit 110 can plan which path to take an image of an imaging point where one satellite can take an image from either of the two paths. Furthermore, the imaging plan generation processing unit 110 of this embodiment can formulate an imaging plan for a plurality of satellites that can be imaged from any of a plurality of paths.
  • the imaging plan generation processing unit 110 of this embodiment selects and copies destination nodes to prevent a closed circuit when combining multiple DAGs expressing the imaging order when imaging with one satellite. , the combined graph is also maintained in the DAG.
  • the imaging plan generation processing unit 110 also performs topological sorting on the combined DAGs to find the longest path. When determining the longest route, the imaging plan generation processing unit 110 calculates a score by taking into consideration overlapping imaging points.
  • the imaging plan generation processing unit 110 removes duplicate points from the obtained longest route.
  • the imaging plan generation processing unit 110 classifies the imaging points remaining on the longest route by satellite, and obtains the imaging order of the imaging points shared by each satellite.
  • the imaging planning system 100 of this embodiment obtains the assignment of imaging points by multiple satellites and the imaging order by finding the longest route from the DAG. Once topological sorting is done, the longest path is quickly obtained from the DAG. That is, the imaging planning system 100 can quickly create imaging plans for multiple satellites.
  • the imaging planning system 100 of this embodiment can be easily implemented using a programming language with simple logic. Furthermore, since most of the processing by the imaging plan generation processing unit 110 can be executed in parallel, if the imaging plan generation processing unit 110 is controlled by a many-core CPU, the imaging plan generation processing unit 110 can perform processing faster. Can be executed.
  • the processes that can be executed in parallel are the processes of steps S121, S122, and S903.
  • the process of step S121 can be executed in parallel for each satellite.
  • the process of step S122 can be executed in parallel for each node.
  • each process in the loop of step S903 can be executed in parallel.
  • the processing by the imaging plan generation processing unit 110 can be easily executed in parallel, so it is easy to speed up the processing.
  • the present invention may be used in the field of earth observation or drone aerial photography.
  • FIG. 13 is an explanatory diagram showing an example of the hardware configuration of the imaging planning system 100 according to the present invention.
  • the imaging planning system 100 shown in FIG. 13 includes a CPU 11, a main storage section 12, a communication section 13, and an auxiliary storage section 14. It also includes an input section 15 for user operation, and an output section 16 for presenting processing results or progress of processing contents to the user.
  • the imaging planning system 100 is realized by software when the CPU 11 shown in FIG. 13 executes a program that provides the functions of each component.
  • each function is realized by software by the CPU 11 loading a program stored in the auxiliary storage unit 14 into the main storage unit 12 and executing it to control the operation of the imaging planning system 100.
  • the imaging planning system 100 shown in FIG. 13 may include a DSP (Digital Signal Processor) instead of the CPU 11.
  • the imaging planning system 100 shown in FIG. 13 may include both the CPU 11 and the DSP.
  • the main storage unit 12 is used as a data work area and a data temporary save area.
  • the main storage unit 12 is, for example, a RAM (Random Access Memory).
  • the communication unit 13 has a function of inputting and outputting data to and from peripheral devices via a wired network or a wireless network (information communication network).
  • the auxiliary storage unit 14 is a non-temporary tangible storage medium.
  • non-temporary tangible storage media include magnetic disks, magneto-optical disks, CD-ROMs (Compact Disk Read Only Memory), DVD-ROMs (Digital Versatile Disk Read Only Memory), and semiconductor memories.
  • the input unit 15 has the function of inputting data and processing instructions.
  • the input unit 15 is, for example, an input device such as a keyboard, a mouse, or a touch panel.
  • the output unit 16 has a function of outputting data.
  • the output unit 16 is, for example, a display device such as a liquid crystal display device, a touch panel, or a printing device such as a printer.
  • each component is connected to a system bus 17.
  • the auxiliary storage unit 14 stores a program for implementing the imaging plan generation processing unit 110.
  • imaging planning system 100 may be implemented with a circuit that includes hardware components such as an LSI (Large Scale Integration) that implements the functions shown in FIG. 1, for example.
  • LSI Large Scale Integration
  • the imaging planning system 100 may be realized by hardware that does not include a computer function using an element such as a CPU.
  • each component may be realized by a general-purpose circuit, a dedicated circuit, a processor, etc., or a combination thereof. These may be constituted by a single chip (for example, the above-mentioned LSI), or may be constituted by a plurality of chips connected via a bus. Part or all of each component may be realized by a combination of the circuits and the like described above and a program.
  • each component of the imaging planning system 100 may be composed of one or more information processing devices including a calculation unit and a storage unit.
  • the plurality of information processing devices, circuits, etc. may be centrally arranged or distributed.
  • information processing devices, circuits, etc. may be implemented as a client and server system, a cloud computing system, or the like, in which each is connected via a communication network.
  • FIG. 14 is a block diagram showing an overview of the imaging planning system according to the present invention.
  • the imaging planning system 20 is an imaging planning system that includes a planning unit 21 (for example, an imaging plan generation processing unit 110) that creates an imaging plan for imaging a plurality of imaging points by a plurality of satellites, and includes:
  • the planning unit 21 generates one DAG by combining DAGs representing the imaging order in which one artificial satellite images a plurality of imaging points so that a predetermined condition is satisfied across the plurality of satellites, Perform topological sorting on one generated DAG and obtain the longest path in the topologically sorted DAG.
  • the planning unit 21 classifies the plurality of imaging points constituting the acquired longest route for each artificial satellite that images them, and executes processing for each artificial satellite to arrange the classified plurality of imaging points in order of imaging time.
  • An imaging plan may be created by this.
  • the planning unit 21 may delete the imaging point with the earlier imaging time among the overlapping imaging points on the acquired longest route.
  • the imaging planning system can quickly formulate an imaging plan using multiple satellites.
  • the predetermined condition may be that no closed path is generated.
  • the imaging planning system can also maintain the combined graph in the DAG.
  • the planning unit 21 updates the score of the node that constitutes one DAG that has been topologically sorted and indicates the imaging point and the input source node of the node for each of all the nodes that constitute one DAG. It may be calculated by
  • Such a configuration allows the imaging planning system to determine the longest path from the DAG in a general manner.
  • the planning unit 21 may calculate the score of the node and the input source node of the node so that the condition that only one of the nodes indicating the same imaging point can be imaged is satisfied.
  • the planning unit 21 may calculate the score of the node and the input source node of the node so that the condition that a plurality of nodes indicating different imaging points can all be imaged at the same imaging time is satisfied.
  • the imaging planning system can solve problems when creating an imaging plan using multiple artificial satellites.
  • a DAG representing the imaging order of one artificial satellite may include multiple columns in which multiple imaging points are arranged in order of imaging time.
  • CPU 12 Main storage section 13 Communication section 14 Auxiliary storage section 15 Input section 16 Output section 17 System bus 20, 100 Imaging plan planning system 21 Planning section 110 Imaging plan generation processing section

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  • Engineering & Computer Science (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • Astronomy & Astrophysics (AREA)
  • General Physics & Mathematics (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Image Processing (AREA)

Abstract

Un système de planification d'imagerie (20) comprend une unité de planification (21) qui planifie un plan d'imagerie pour imager une pluralité de points d'imagerie à l'aide d'une pluralité de satellites artificiels, l'unité de planification (21) générant un DAG par combinaison de DAG représentant l'ordre d'imagerie dans lequel un satellite artificiel image la pluralité de points d'imagerie de telle sorte qu'une condition prédéterminée est satisfaite pour la pluralité de satellites artificiels, effectue un tri topologique sur le DAG généré, et acquiert le trajet le plus long dans un DAG pour lequel est effectué un tri topologique.
PCT/JP2023/012263 2022-04-22 2023-03-27 Système de planification d'imagerie et procédé de planification d'imagerie WO2023203970A1 (fr)

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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060287842A1 (en) * 2003-09-22 2006-12-21 Advanced Structure Monitoring, Inc. Methods of networking interrogation devices for structural conditions
JP2018522775A (ja) * 2015-07-28 2018-08-16 エアバス・ディフェンス・アンド・スペース・エスアーエス 宇宙機による地上領域の画像取得を計画する方法

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060287842A1 (en) * 2003-09-22 2006-12-21 Advanced Structure Monitoring, Inc. Methods of networking interrogation devices for structural conditions
JP2018522775A (ja) * 2015-07-28 2018-08-16 エアバス・ディフェンス・アンド・スペース・エスアーエス 宇宙機による地上領域の画像取得を計画する方法

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